Learning from incomplete data with infinite imputations

Proceedings of the 25th International Conference on Machine Learning

Volumn , Issue , 2008, Pages 232-239

  Dick, Uwe ^a   Haider, Peter ^a   Scheffer, Tobias ^a  

^a MAX PLANCK INSTITUTE FOR INFORMATICS   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

BENCHMARKING; MACHINE LEARNING; EDUCATION; LEARNING SYSTEMS; ROBOT LEARNING;

ATTRIBUTE VALUES; DECISION FUNCTIONS; FREE PARAMETERS; INCOMPLETE DATA; JOINT OPTIMIZATION; MISSING VALUES; MULTIPLE SOURCE; OPTIMAL SOLUTIONS;

LEARNING ALGORITHMS;

ATTRIBUTE VALUES; BENCHMARK DATUM; DECISION FUNCTIONS; E-MAIL SPAM; EMPIRICAL RESULTS; FREE PARAMETERS; INCOMPLETE DATUM; JOINT OPTIMIZATIONS; MISSING VALUES; MULTIPLE SOURCES; OPTIMAL SOLUTIONS; TRAINING DATUM;

EID: 56449102221     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1390156.1390186     Document Type: Conference Paper

References (8)

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4. Micchelli, C., & Pontil, M. (2007). Feature space perspectives for learning the kernel. Machine Learning, 66.
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8. Williams, D., Liao, X., Xue, Y., & Carin, L. (2005). Incomplete-data classification using logistic regression. Proceedings of the 22nd International Conference on Machine learning.